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Research Papers

Compressible Direct Numerical Simulation of Low-Pressure Turbines—Part II: Effect of Inflow Disturbances

[+] Author and Article Information
Vittorio Michelassi

Professor
Mem. ASME
Aero-Thermal Systems,
GE Global Research,
Munich D-85748, Germany

Li-Wei Chen

Research Fellow
Aerodynamics and Flight Mechanics
Research Group,
Faculty of Engineering
and the Environment,
University of Southampton,
Southampton SO17 1BJ, UK

Richard Pichler

Aerodynamics and Flight Mechanics
Research Group,
Faculty of Engineering
and the Environment,
University of Southampton,
Southampton SO17 1BJ, UK

Richard D. Sandberg

Professor
Mem. ASME
Aerodynamics and Flight Mechanics
Research Group,
Faculty of Engineering and the Environment,
University of Southampton,
Southampton SO17 1BJ, UK
e-mail: R.D.Sandberg@soton.ac.uk

1Corresponding author.

Contributed by the International Gas Turbine Institute (IGTI) of ASME for publication in the JOURNAL OF TURBOMACHINERY. Manuscript received August 20, 2014; final manuscript received September 16, 2014; published online December 29, 2014. Editor: Ronald S. Bunker.

J. Turbomach 137(7), 071005 (Jul 01, 2015) (12 pages) Paper No: TURBO-14-1212; doi: 10.1115/1.4029126 History: Received August 20, 2014; Revised September 16, 2014; Online December 29, 2014

In the present paper, direct numerical simulation (DNS) studies of the compressible flow in the T106 linear cascade have been carried out. Various environmental variables, i.e., background turbulence level, frequency of incoming wakes, and Reynolds number, and a combination of these were considered for a total of 12 fully resolved simulations. The mechanisms dictating the observed flow phenomena, including the mixing and distortion of the incoming wakes, wake/boundary layer interaction, and boundary layer evolution impact on profile loss generation, are studied systematically. A detailed loss generation analysis allows the identification of each source of loss in boundary layers and flow core. Particular attention is devoted to the concerted impact of wakes distortion mechanics and the intermittent nature of the unsteady boundary layer. Further, the present study examines the validity of the Boussinesq eddy viscosity assumption, which invokes a linear stress–strain relationship in commonly used RANS models. The errors originating from this assumption are scrutinized with both time and phase-locked averaged flow fields to possibly identify shortcomings of traditional RANS models.

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References

Figures

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Fig. 4

Pressure coefficient (a) and wall shear distribution (b) on the blade surface at Re2is = 60,000. Here, Cax is the axial chord length.

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Fig. 3

Instantaneous contours of the spanwise component of vorticity (−50 to 50) in the midspan (x, y) plane for Fred = 0 (top left), Fred = 0.31 (top right), Fred = 0.61 (bottom left), and Fred = 1.22 (bottom right) with Tu = 0.5%, Re2is = 60,000

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Fig. 2

Isosurfaces of instantaneous second invariant of the velocity-gradient tensor (Q = 500) colored by velocity magnitude at various time instants for Fred = 0.31, Tu = 0.5%, Re2is = 60,000

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Fig. 1

Sketch of moving bars and the blade geometry

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Fig. 5

Comparison of Re2is = 60,000 and Re2is = 100,000: (a) pressure coefficient and (b) wall shear distribution

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Fig. 6

Length of separation bubble: (a) top, TE separation bubble; (b) bottom, LE separation bubble

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Fig. 7

Space–time diagrams of momentum thickness θ and the variation at the TE (s ∼ 1.308): (a) top, Fred = 0.31, Tu = 0.5%, Re2is = 60,000; (b) mid, Fred = 0.61, Tu = 0.5%, Re2is = 60,000; (c) bottom, Fred = 1.22, Tu = 0.5%, Re2is = 60,000

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Fig. 8

Two phase-averaged snapshots of TKE (a) and (c), top, and TKE production terms (b) and (d), bottom, with the contour levels between 0 (blue) and 0.05 (red): ϕ = 0 and 0.4 and 0.8 (Fred = 0.31, Tu = 0.5% and Re2is = 60,000)

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Fig. 9

Two phase-averaged snapshots of TKE (a) and (c), top, and TKE production terms (b) and (d), bottom, with the contour levels between 0 (blue) and 0.05 (red): φ=0 and 0.4 (Fred = 0.61, Tu = 0.5% and Re2is = 60,000)

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Fig. 10

Comparison of the wake stagnation pressure loss profiles with reference data: (a) Re2is = 60,000 and (b) Re2is = 100,000. Here, “P” denotes pressure side and “S” suction side.

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Fig. 11

Stagnation pressure losses calculated with mixed-out quantities

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Fig. 13

Denton's loss coefficient (a), top, and the difference from mixed-out losses (b), bottom

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Fig. 12

Terms of the TE profile loss in Eq. (1) suggested by Denton [19]: (a) the base pressure loss TERM 1; (b) the mixed-out loss of the boundary layer (or the momentum deficit loss) TERM 2; and (c) the combined blockage loss TERM 3

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Fig. 14

Comparison of the deviation Δ, wake mixing η1 and distortion losses η2: (a), top, Tu = 0.5%, Re2is = 60,000; (b) Tu = 3.2%, Re2is = 60,000. The sketch shows the locations of the profiles extracted outside of the boundary layer.

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Fig. 15

Minimum Reynolds stress error et,min using Boussinesq approximation at Re2is = 60,000 and Tu = 3.2%

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Fig. 16

Reynolds stress error et,kε using kε model with the Boussinesq approximation at Re2is = 60,000 at a reduced frequency of 0.61 at the same time instant as in Fig. 9(d)

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Fig. 17

Normalized Reynolds stresses error using the Boussinesq approximation at Re2is = 60,000 and Tu = 3.2%

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